monitoring-observability
Set up monitoring, logging, and observability for applications and infrastructure. Use when implementing health checks, metrics collection, log aggregation, or alerting systems. Handles Prometheus, Grafana, ELK Stack, Datadog, and monitoring best practices.
Install with Tessl CLI
npx tessl i github:supercent-io/skills-template --skill monitoring-observability86
Quality
82%
Does it follow best practices?
Impact
94%
1.14xAverage score across 3 eval scenarios
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-crafted skill description that excels across all dimensions. It provides specific capabilities, includes an explicit 'Use when...' clause with natural trigger terms, names concrete tools, and carves out a distinct monitoring/observability niche. The description uses proper third-person voice throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'monitoring, logging, and observability', 'health checks, metrics collection, log aggregation, alerting systems' and names specific tools (Prometheus, Grafana, ELK Stack, Datadog). | 3 / 3 |
Completeness | Clearly answers both what ('Set up monitoring, logging, and observability') and when ('Use when implementing health checks, metrics collection, log aggregation, or alerting systems') with explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'monitoring', 'logging', 'observability', 'health checks', 'metrics', 'alerting', plus specific tool names like 'Prometheus', 'Grafana', 'ELK Stack', 'Datadog'. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche focused on observability/monitoring domain with distinct triggers (Prometheus, Grafana, ELK, Datadog, metrics, alerting) that are unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill excels at actionability with comprehensive, executable code examples covering the full monitoring stack. However, it's overly long for a SKILL.md file, lacking validation checkpoints between steps and including unnecessary metadata/placeholder sections. The content would benefit from splitting detailed configurations into separate files and adding explicit verification steps.
Suggestions
Add validation checkpoints between steps (e.g., 'Verify /metrics endpoint returns data: curl localhost:3000/metrics | head' before proceeding to Prometheus configuration)
Move detailed configurations (alert_rules.yml, dashboard.json, full Winston setup) to separate reference files and link to them from the main skill
Remove empty example placeholders and the metadata section which adds no value for Claude
Remove the 'When to use this skill' section - Claude understands when monitoring is needed
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill provides substantial executable code which is valuable, but includes some unnecessary verbosity like the metadata section, empty example placeholders, and the 'When to use this skill' section that explains obvious use cases Claude would already understand. | 2 / 3 |
Actionability | Excellent executable code examples throughout - complete TypeScript instrumentation, full Prometheus config, alert rules, Winston logging setup, Grafana dashboard JSON, and health check implementation. All code is copy-paste ready. | 3 / 3 |
Workflow Clarity | Steps are numbered and sequenced (Step 1-5), but there are no validation checkpoints or feedback loops. For a monitoring setup that could affect production systems, there should be explicit verification steps (e.g., 'verify metrics endpoint returns data before configuring Prometheus'). | 2 / 3 |
Progressive Disclosure | Content is reasonably organized with clear sections, but the skill is monolithic with ~300 lines of inline code. The Grafana dashboard JSON and detailed alert rules could be split into separate reference files, with the main skill providing overview and links. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Reviewed
Table of Contents
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